Executive Development Programme in GPU computing for data science
-- ViewingNowThe Executive Development Programme in GPU Computing for Data Science is a certificate course designed to provide learners with essential skills in GPU-accelerated computing. This programme is crucial in today's data-driven world, where GPU computing has become a critical tool for handling big data and complex computations.
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⢠Introduction to GPU computing: Understanding the basics of GPU architecture, CUDA programming model, and parallel computing concepts.
⢠Data management in GPU computing: Learning efficient data management techniques, data transfer between CPU and GPU, and optimizing memory usage.
⢠Linear algebra and matrix operations: Implementing linear algebra algorithms and matrix operations on GPU for data science applications.
⢠Deep learning frameworks on GPU: Exploring popular deep learning frameworks such as TensorFlow and PyTorch, and their integration with GPU computing.
⢠Optimization techniques for GPU computing: Understanding various optimization techniques such as cuDNN, TensorRT, and loop unrolling for improving performance.
⢠Machine learning algorithms on GPU: Implementing machine learning algorithms such as decision trees, random forests, and support vector machines on GPU.
⢠Data visualization using GPU: Learning to visualize large datasets using GPU-accelerated libraries such as matplotlib and seaborn.
⢠Real-world applications of GPU computing in data science: Exploring case studies and real-world applications of GPU computing in data science, such as image recognition, natural language processing, and recommender systems.
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